P. Maes

Publications108
h-index30
Citations4,726
Highly Influential Citations218
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Agents that reduce work and information overload
  • 1,022
  • 49
Toward the Evolution of Dynamical Neural Networks for Minimally Cognitive Behavior
TLDR
This paper sketches one such agent, and presents the results of preliminary experiments on the evolution of dynamical neural networks for visually-guided orientation, object discrimination and accurate pointing with a simple manipulator to objects appearing in its field of view. Expand
  • 283
  • 49
Concepts and experiments in computational reflection
  • P. Maes
  • Computer Science
  • OOPSLA
  • 1 December 1987
TLDR
This paper brings some perspective to various concepts in computational reflection. Expand
  • 431
  • 12
Cooperating Mobile Agents for Dynamic Network Routing
TLDR
A method for using a collection of cooperating mobile agents to solve routing problems for dynamic, peer-to-peer networks. Expand
  • 194
  • 10
A Study of Territoriality: The Role of Critical Mass in Adaptive Task Division
TLDR
This work demonstrates the application of the behavior-based approach to generating ethologically-inspired adaptive adaptive foraging using a division of labor into exclusive spatial territories. Expand
  • 99
  • 10
Evolving agents for personalized information filtering
  • B. Sheth, P. Maes
  • Computer Science
  • Proceedings of 9th IEEE Conference on Artificial…
  • 1 March 1993
TLDR
This paper describes how techniques from artificial life can be used to evolve a population of personalized information filtering agents to make a personalized selection of news articles from the newsgroups. Expand
  • 294
  • 8
Behavior-based artificial intelligence
  • P. Maes
  • Computer Science
  • 9 August 1993
  • 131
  • 7
Robotic “Food” Chains: Externalization of State and Program for Minimal-Agent Foraging
TLDR
This paper describes experiments inspired by theoretical work on information invariants ([Donald 1995], [Donald et al 1994]), a means of comparison and a methodology for design of single- and multi-agent systems. Expand
  • 88
  • 7
Emergent Hierarchical Control Structures: Learning Reactive/Hierarchical Relationships in Reinforcement Environments
  • 78
  • 7
The Evolution of Communication Schemes Over Continuous Channels
TLDR
A method by which a set of agents can evolve a communication scheme to solve a given task without a priori native structure in place. Expand
  • 52
  • 6